The interconnection network is one of the most basic components of a massively parallel computer system. Such systems consist of hundreds or thousands of processors interconnected to work cooperatively on computations. One of the central problems in parallel computing is the task of mapping a collection of processes onto the processors and routing network of a parallel machine. Once this mapping is done, it is critical to schedule computations within and communication among processors so that the necessary inputs for a process are available where and when the process is scheduled to be computed. This book contains the refereed proceedings of a DIMACS Workshop on Massively Parallel Computation, held in February 1994. The workshop brought together researchers from universities and laboratories, as well as practitioners involved in the design, implementation, and application of massively parallel systems. Focusing on interconnection networks of parallel architectures of today and of the near future, the book includes topics such as network topologies, network properties, message routing, network embeddings, network emulation, mappings, and efficient scheduling.

This book constitutes the thoroughly refereed post-proceedings of the 4th International Conference on Parallel Processing and Applied Mathematics, PPAM 2002, held in Naleczow, Poland, in September 2001. The 101 papers presented were carefully reviewed and improved during two rounds of reviewing and revision. The book offers topical sections on distributed and grid architectures, scheduling and load balancing, performance analysis and prediction, parallel non-numerical algorithms, parallel programming, tools and environments, parallel numerical algorithms, applications, and evolutionary computing and neural networks.

Parallel Population and Parallel Human Proposes a new paradigm to investigate an individual’s cognitive deliberation in dynamic human-machine interactions Today, intelligent machines enable people to interact remotely with friends, family, romantic partners, colleagues, competitors, organizations, and others. Virtual reality (VR), augmented reality (AR), artificial intelligence (AI), mobile social media, and other technologies have been driving these interactions to an unprecedented level. As the complexity in system control and management with human participants increases, engineers are facing challenges that arise from the uncertainty of operators or users. Parallel Population and Parallel Human: A Cyber-Physical Social Approach presents systemic solutions for modeling, analysis, computation, and management of individuals’ cognition and decision-making in human-participated systems, such as the MetaVerse. With a virtual-real behavioral approach that seeks to actively prescribe user behavior through cognitive and dynamic learning, the authors present a parallel population/human model for optimal prescriptive control and management of complex systems that leverages recent advances in artificial intelligence. Throughout the book, the authors address basic theory and methodology for modeling, describe various implementation techniques, highlight potential acceleration technologies, discuss application cases from different fields, and more. In addition, the text: Considers how an individual’s behavior is formed and how to prescribe their behavioral modes Describes agent-based computation for complex social systems based on a synthetic population from realistic individual groups Proposes a universal algorithm applicable to a wide range of social organization types Extends traditional cognitive modeling by utilizing a dynamic approach to investigate cognitive deliberation in highly time-variant tasks Presents a new method that can be used for both large-scale social systems and real-time human-machine interactions without extensive experiments for modeling Parallel Population and Parallel Human: A Cyber-Physical Social Approach is a must-read for researchers, engineers, scientists, professionals, and graduate students who work on systems engineering, human-machine interaction, cognitive computing, and artificial intelligence.

This book presents a hybrid static-dynamic approach for efficient performance analysis of parallel applications on HPC systems. Performance analysis is essential to finding performance bottlenecks and understanding the performance behaviors of parallel applications on HPC systems. However, current performance analysis techniques usually incur significant overhead. Our book introduces a series of approaches for lightweight performance analysis. We combine static and dynamic analysis to reduce the overhead of performance analysis. Based on this hybrid static-dynamic approach, we then propose several innovative techniques for various performance analysis scenarios, including communication analysis, memory analysis, noise analysis, computation analysis, and scalability analysis. Through these specific performance analysis techniques, we convey to readers the idea of using static analysis to support dynamic analysis. To gain the most from the book, readers should have a basic grasp of parallel computing, computer architecture, and compilation techniques.

This book constitutes the proceedings of the 11th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2014, held in Ilan, Taiwan, in September 2014. The 42 full papers and 24 poster papers presented were carefully reviewed and selected from 196 submissions. They are organized in topical sections on systems, networks, and architectures, parallel and multi-core technologies, virtualization and cloud computing technologies, applications of parallel and distributed computing, and I/O, file systems, and data management.

This book constitutes the strictly refereed post-workshop proceedings of the International Workshop on Job Scheduling Strategies for Parallel Processing, held in conjunction with IPPS '96 symposium in Honolulu, Hawaii, in April 1996. The book presents 15 thoroughly revised full papers accepted for inclusion on the basis of the reports of at least five program committee members. The volume is a highly competent contribution to advancing the state-of-the-art in the area of job scheduling for parallel supercomputers. Among the topics addressed are job scheduler, workload evolution, gang scheduling, multiprocessor scheduling, parallel processor allocation, and distributed memory environments.

Patterns and Skeletons for Parallel and Distributed Computing is a unique survey of research work in high-level parallel and distributed computing over the past ten years. Comprising contributions from the leading researchers in Europe and the US, it looks at interaction patterns and their role in parallel and distributed processing, and demonstrates for the first time the link between skeletons and design patterns. It focuses on computation and communication structures that are beyond simple message-passing or remote procedure calling, and also on pragmatic approaches that lead to practical design and programming methodologies with their associated compilers and tools. The book is divided into two parts which cover: skeletons-related material such as expressing and composing skeletons, formal transformation, cost modelling and languages, compilers and run-time systems for skeleton-based programming.- design patterns and other related concepts, applied to other areas such as real-time, embedded and distributed systems. It will be an essential reference for researchers undertaking new projects in this area, and will also provide useful background reading for advanced undergraduate and postgraduate courses on parallel or distributed system design.

New approaches to parallel computing are being developed that make better use of the heterogeneous cluster architecture Provides a detailed introduction to parallel computing on heterogenous clusters All concepts and algorithms are illustrated with working programs that can be compiled and executed on any cluster The algorithms discussed have practical applications in a range of real-life parallel computing problems, such as the N-body problem, portfolio management, and the modeling of oil extraction

If you have a working knowledge of Haskell, this hands-on book shows you how to use the language’s many APIs and frameworks for writing both parallel and concurrent programs. You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions. Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented: Express parallelism in Haskell with the Eval monad and Evaluation Strategies Parallelize ordinary Haskell code with the Par monad Build parallel array-based computations, using the Repa library Use the Accelerate library to run computations directly on the GPU Work with basic interfaces for writing concurrent code Build trees of threads for larger and more complex programs Learn how to build high-speed concurrent network servers Write distributed programs that run on multiple machines in a network

This book constitutes the refereed proceedings of the 5th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2007, held in Niagara Falls, Canada, in August 2007. The 83 revised full papers presented together with three keynote are cover algorithms and applications, architectures and systems, datamining and databases, fault tolerance and security, middleware and cooperative computing, networks, as well as software and languages.